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Towards characterizing bug fixes through dependency-level changes in Apache Java open source projects

science China(Information sciences) 2022年第7期65卷 102-120页

作者： Di CUI Lingling FAN Sen CHEN Yuanfang CAI Qinghua ZHENG Yang LIU Ting LIU School of Computer Science and Technology Xi'an Jiaotong University College of Cyber Science Nankai University College of Intelligence and Computing Tianjin University Department of Computer Science Drexel University School of Computer Science and Engineering Nanyang Technological University School of Cyber Science and Engineering Xi'an Jiaotong University

The complexity and diversity of bug fixes require developers to understand bug fixes from multiple perspectives in addition to fine-grained code changes. The dependencies among files in a software system are an important dimension to inform software quality. Recent studies have revealed that most bug-prone files are always architecturally connected with dependencies, and as one of the best practices in the industry,changes in dependencies should be avoided or carefully made during bug fixing. Hence, in this paper, we take the first attempt to understand bug fixes from the dependencies perspective, which can complement existing code change perspectives. Based on this new perspective, we conducted a systematic and comprehensive study on bug fixes collected from 157 Apache open source projects, involving 140456 bug reports and182621 bug fixes in total. Our study results show that a relatively high proportion of bug fixes(30%) introduce dependency-level changes when fixing the corresponding 33% bugs. The bugs, whose fixes introduce dependency-level changes, have a strong correlation with high priority, large fixing churn, long fixing time,frequent bug reopening, and bug inducing. More importantly, patched files with dependency-level changes in their fixes, consume much more maintenance costs compared with those without these changes. We further summarized three representative patch patterns to explain the reasons for the increasing costs. Our study unveils useful findings based on qualitative and quantitative analysis and also provides new insights that might benefit existing bug prediction techniques. We release a large set of benchmarks and also implement a prototype tool to automatically detect dependency-level changes from bug fixes, which can warn developers and remind them to design a better fix.

关键词： empirical software engineering software maintenance software evolution software architecture software design

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Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

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Chinese Physics B 2024年第4期33卷 418-433页

作者：周新卫蒋东华 Jean De Dieu Nkapkop Musheer Ahmad Jules Tagne Fossi Nestor Tsafack 吴建华 Department of Information Engineering Gongqing CollegeNanchang UniversityJiujiang 332020China School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 511400China Department of Electrical Engineering and Industrial Computing University Institute of TechnologyDoualaCameroon Department of Computer Engineering Jamia Millia IslamiaNew Delhi 110025India Department of Physics Faculty of ScienceUniversity of YaoundeCameroon Electrical Engineering Department and Industrial Computing of ISTAMA University of DoualaDoualaCameroon

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

关键词： cellular neural network memristor hardware circuit compressive sensing privacy data protection

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A Hybrid Approach of Spider Monkey Optimization with Taylor Series for Optimal Routing in Wireless Sensor Network 7

A Hybrid Approach of Spider Monkey Optimization with Taylor ...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Sindhuja, M. Srm Institute of Science And Technology School of Computing College of Engineering And Technology Department of Computing Technologies Chennai Tamil Nadu Kattankulathur India

ISBN: (纸本)9798350359299

Clustering that facilitates routing protocols has been created in recent years to cut down on energy usage and increase the lifespan of WSNs. The LEACH cluster is well-known among WSNs. The LEACH selects a few sensor nodes at random from each cluster. Cluster heads (CHs) are the aforementioned nodes. Cluster members are the sensor nodes that make up each CH. CHs hold up extra load to coordinate diverse tasks during the cluster. Energy usage and overall network performance can both suffer if the wrong CHs are selected for the LEACH. Therefore, a significant factor in extending the WSN's lifetime is selecting an appropriate CH and an efficient routing algorithm. This work introduces a new approach to CH selection and optimal routing in WSN, combining the Spider monkey optimization technique with a Taylor-based gravitational search algorithm. The CHs are selected, and cluster-based routing algorithms are developed using Spider Monkey Optimization (SMO). The sensor nodes are first organized into clusters, with the maximum competent node being the cluster head. From there, communication is sent across several nodes in a multi-hop fashion. Taylor dependent gravitational search method (TDGSM) is introduced which uses the taylor series along with gravitational search method to find the optimal routing. The suggested algorithm has achieved superior results when compared to the existing methods. © 2024 IEEE.

关键词： Sensor nodes

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Oral Vision: Advanced Image Recognition for Oral Cancer 5

Oral Vision: Advanced Image Recognition for Oral Cancer

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Ghosh, Joita Mishra, Khushi Sindhuja, M. Nagadevi, S. Anand, M. School of Computing College of Engineering and Technology SRM Institute of Science and Technology Dept. of Computing Technologies Tamil Nadu Kattankulathur India

ISBN: (纸本)9798331530013

Cancer that affects the lining of the mouth, lips, or upper throat is called oral cancer. Other names for it include tongue cancer, mouth cancer, and oral cavity cancer. There is an urgent need for early cancer detection due to the rise in cancer cases in all age groups. Alcohol consumption and tobacco usage are risk factors. The risk of oral cancer is fifteen times higher for people who use both alcohol and tobacco than for people who do not. This paper presents a deep learning-based technique that uses the ResNet50 convolution neural network model to classify the images of malignant and non-malignant oral cell images. To enhance the pretrained ResNet50 model's capacity to differentiate malignant and benign samples, it was trained using a dataset of histopathological oral tissue pictures. A special virtual voice assistant has also been integrated along with the model to make it more assistive for all kinds of users. In order to track the advancement of these methods, this paper also analyses how combining NLP with point-of-care tools makes use of a variety of algorithms and sets. © 2024 IEEE.

关键词： Lung cancer

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E-Waste Alchemy: A Unified Solution for Recycling and Sustainability 5

E-Waste Alchemy: A Unified Solution for Recycling and Sustai...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Sharma, Vansh Sameer, Md Sindhuja, M. Nagadevi, S. Anand, M. School of Computing College of Engineering and Technology SRM Institute of Science and Technology Dept. of Computing Technologies Tamil Nadu Kattankulathur India

ISBN: (纸本)9798331530013

Through user-centric solutions and advanced features, E-Waste Alchemy is an innovative platform that aims to transform the administration of electronic waste (e-waste). The Recycle Centre on the platform is comprehensive, allowing users to specify the brand and model of laptops, smartphones, and a variety of accessories in order to schedule and select the retrieval. E-Waste Alchemy further improves user convenience by enabling real-time tracking of nearby recyclers based on the user's current location. Furthermore, the platform employs predictive analytics to determine the market values of the components contained within each device, including plastic, aluminum, and nickel. The responsible disposal of e-waste is promoted by this predictive feature, which also contributes to environmental sustainability by optimizing recycling processes. E-Waste Alchemy is a forward-thinking and adaptable solution that facilitates the administration of e-waste and promotes a circular economy. © 2024 IEEE.

关键词： Circular economy

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Enhancing Healthcare AI Sensitivity through Affective computing: Analyzing Human Emotions 1

Enhancing Healthcare AI Sensitivity through Affective Comput...

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1st IEEE International Conference on Advances in computing, Communication and Networking, ICAC2N 2024

作者： Singh, Rahul Kumar, Avadhesh Sagar, Shraddha Sharma, Vishnu Galgotias University School of Computing Science and Engineering Greater Noida India ITS Engineering College Department of Computer Science Engineering Greater Noida India

ISBN: (纸本)9798350356816

Affective computing (AC), also known as emotion AI, is a concept that applies modern technology to help systems to recognize and process human emotions and their feelings. Several uses of affective computing have been demonstrated, including marketing, healthcare, driving assistance, and education. Linear Support vector machines (SVM), k-nearest neighbor (k-NN), Hidden Markov models (HMMs), Gaussian mixture models (GMM), discriminate classifiers (LDC), decision tree algorithms and artificial neural networks (ANN), are the classifiers that are most frequently used in research on identifying and categorizing human emotions. Selecting the right classifier can significantly increase the system's overall efficiency, as numerous studies have conclusively demonstrated. Through use of cameras, microphones, skin sensors, or other devices, affective computing gathers signals from human users, gathering data on their facial expressions, voice tones, gestures, and other characteristics that can hint at their emotional states. The system deduces the user's emotional state from those data points. This study emphasizes on the fundamentals of computing emotions. © 2024 IEEE.

关键词： Support vector machines

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A hybrid personality-aware recommendation system based on personality traits and types models

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Journal of Ambient Intelligence and Humanized computing 2023年第9期14卷 12775-12788页

作者： Dhelim, Sahraoui Chen, Liming Aung, Nyothiri Zhang, Wenyin Ning, Huansheng School of Computer Science University College Dublin Dublin Ireland School of Computing Ulster University Belfast United Kingdom School of Information Science and Engineering Linyi University Linyi China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

Personality-aware recommendation systems have been proven to achieve high accuracy compared to conventional recommendation systems. In addition to that, personality-aware recommendation systems could help alleviate cold start and data sparsity problems by adding the user’s personality traits in the recommendation process. The majority of the literature works used Big-Five personality model to represent the user’s personality, this is due to the popularity of Big-Five model in the literature of psychology. However, from personality computing perspective, the choice of the most suitable personality model that satisfy the requirements of the recommendation application and the recommended content type still needs further investigation. In this paper, we study and compare four personality-aware recommendation systems based on different personality models, namely Big-Five traits model, Eysenck model and HEXACO model from the personality traits theory, and Myers–Briggs Type Indicator (MPTI) from the personality types theory. Furthermore, we propose a hybrid personality model for recommendation that takes advantage of the personality traits models, as well as the personality types models. Through extensive experiments on recommendation dataset, we prove the efficiency of the proposed model, especially in cold start settings. Our proposed hybrid personality-aware recommendation model improves the precision and recall in cold start settings by 21% and 18% respectively compared to the widely used Big-Five traits model. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Recommender systems

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Design of Approximate Multiplier using Highly Compressed 5_2 Counter 6

Design of Approximate Multiplier using Highly Compressed 5_2...

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6th International Conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Nelmin, Bathlin N. Shaji, R.S. Hariprasad, S. Shettygari, Sudeshna Vasan, J.K. Vijayan, V. Department of Electronics and Communication Engineering University College of Engineering Nagercoil India Department of Computer Science and Engineering St. Xavier’s Catholic College of Engineering Nagercoil India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (纸本)9798331522667

Approximate computing effectively impacts low-power VLSI circuits by reducing circuit overhead. It introduces minimal error in the output, which does not significantly affect the application. This paper proposes an approximate multiplier constructed using 5_3 and 5_2 counters. The proposed 5_2 counter delivers two outputs instead of three, thereby achieving 60% compression. The overhead of the 5_2 counter circuit is reduced, achieving a power delay product (PDP) improvement of 18%. This reduction comes with an addition of an 6% error rate. The newly designed multiplier has less delay, where the Mean error distance (MED) is kept as low as possible. The complexity of the 5_2 counter is also reduced since the counter uses only a full adder and three gates. This is achieved by applying various error optimization mechanisms. The error parameters, (i) Error Distance (ED), and (ii) Mean Error Distance (MED) are analyzed and compared with existing works. The proposed multipliers are involved in image contrast application with better Peak Signal to Noise Ratio (PSNR) value. © 2025 IEEE.

关键词： Delay circuits

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Multi-component liquid-infused systems:a new approach to functional coatings

Industrial Chemistry & Materials

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Industrial Chemistry & Materials 2024年第3期2卷 378-392页

作者： Zachary Applebee Caitlin Howell Department of Chemical and Biomedical Engineering Maine College of Engineering and ComputingUniversity of MaineME 04469USA Graduate School of Biomedical Science and Engineering University of MaineME 04469USA

Antifouling liquid-infused surfaces have generated interest in multiple fields due to their diverse applications in industry and *** nearly all reports to date,the liquid component consists of only one chemical ***,unlike traditional solid surfaces,the unique nature of liquid surfaces holds the potential for synergistic and even adaptive functionality simply by including additional elements in the liquid *** this work,we explore the concept of multi-component liquid-infused systems,in which the coating liquid consists of a primary liquid and a secondary component or components that provide additional *** ease of understanding,we categorize recently reported multi-component liquid-infused surfaces according to the size of the secondary components:molecular scale,in which the secondary components are molecules;nanoscale,in which they are nanoparticles or their equivalent;and microscale,in which the additional components are micrometer size or *** present examples at each scale,showing how introducing a secondary element into the liquid can result in synergistic effects,such as maintaining a pristine surface while actively modifying the surrounding environment,which are difficult to achieve in other surface *** review highlights the diversity of fabrication methods and provides perspectives on future research *** secondary components into the liquid matrix of liquid-infused surfaces is a promising strategy with significant potential to create a new class of multifunctional materials.

关键词： Active surfaces Antimicrobial Antifouling Interfaces Sensing surfaces

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A Novel Attention-Based Method for Integrating Facial and Speech Features in Emotion Recognition 2

A Novel Attention-Based Method for Integrating Facial and Sp...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Singh, Rahul Sagar, Shraddha Kumar, Avadhesh Sharma, Vishnu Galgotias University School of Computing Science & Engineering Greater Noida India Its Engineering College Department of Computer Science Engineering Greater Noida India

ISBN: (纸本)9798350388916

Our research introduces a novel approach for recognizing multiple emotions by leveraging perspective-based methods. This technique integrates facial features and speech characteristics obtained from different encoders to pinpoint the most significant attributes. The distinct characteristics of speech and facial expressions, along with effective size management, prove to be highly beneficial. By concentrating on specific components, the system enhances overall accuracy. Images of facial features are captured from both low and high angles to ensure a comprehensive representation. These techniques are merged through a fusion mesh, producing several feature vectors that are subsequently utilized in the classification stage for sensitivity analysis. When tested with both data sets, this algorithm surpassed existing models, achieving a weighted accuracy (WA) of 90.3%. © 2024 IEEE.

关键词： Attention-Based Method Emotion Classification Facial and Speech Features Fusion Network Multimodal Emotion Recognition Weighted Accuracy

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